Updated the documentation with the related manuscript.
The print method of the output of
lav_betaselect() has a column to indicate whether a
parameter is unstandardized. (0.1.3.1)
The computation of the standardized solution with bootstrapping now supports parallel processing. (0.1.3.2)
lav_betaselect() can also compute the “standardized”
intercepts, though in the same way lavaan does, by dividing
an intercept by the standard deviation of the outcome variable (the
y variable). This can be enabled by setting
std_intercept to TRUE (FALSE by
default). (0.1.2.1)lav_betaselect() will no longer check whether variables
involved in a product term have been mean-centered by default (but can
still be enabled if necessary). The coefficient of the so-called “main
effect” term of these variables will now be computed correctly even
without mean-centering. (0.1.2.1, 0.1.2.2)lav_betaselect() will not compute the coefficients of
covariances and variances that involve a product term, if the variables
involved are not mean-centered. Without mean-centering, it is impossible
to compute them if the joint distribution of the variables is not
multivariate normal. (0.1.2.1)lav_betaselect(): The standardized coefficients of the
component variables of a product term are incorrect if mean-centering is
not done. For now, lav_betaselect() will check whether they
are mena-centered. If not, it will raise an error and suggest users to
mean-center the involved variables first. (0.1.1)
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